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Another version - Scott Aaronson
Another version - Scott Aaronson

... Key point: factoring is not believed to be NP-complete! And today, we don’t believe quantum computers can solve NP-complete problems in polynomial time in general (though not surprisingly, we can’t prove it) Bennett et al. 1997: “Quantum magic” won’t be enough If you throw away the problem structur ...
Physics 411: Introduction to Quantum Mechanics
Physics 411: Introduction to Quantum Mechanics

Physics PHYS 356 Spring Semester  2013 Quantum Mechanics (4 credit hours)
Physics PHYS 356 Spring Semester 2013 Quantum Mechanics (4 credit hours)

... In this class I would like for you to develop a “quantum worldview” – by which I mean that I would like to re-examine some of the concepts that you have previously, in classes like classical mechanics and electricity and magnetism, held as starting assumptions. In doing this, you will need to learn ...
Quantum plasmonics
Quantum plasmonics

... enable the confinement of light to scales far below that of conventional optics; suffer from large losses Quantum plasmonics build devices that can exploit lossy nature for controlling dissipative quantum dynamics combine modern plasmonics with quantum optics, study the fundamental physics of surfac ...
LT1: Electron.NOTES - Simpson County Schools
LT1: Electron.NOTES - Simpson County Schools

... Why did the wave model of light need a revision? ________________________________________________________________________________________________________ ...
Computational Complexity and Fundamental Physics
Computational Complexity and Fundamental Physics

Study Questions and Problems
Study Questions and Problems

Geometry, Physics, and Representation Theory Traces of intertwiners for quantum affine and
Geometry, Physics, and Representation Theory Traces of intertwiners for quantum affine and

Quantum Mechanics is Real Black Magic Calculus
Quantum Mechanics is Real Black Magic Calculus

... I think it is safe to say that no one understands Quantum Mechanics One does not, by knowing all the physical laws as we know them today, immediately obtain an understanding of anything much. The more you see how strangely Nature behaves, the harder it is to make a model that explains how even the s ...
Projects - Department of Computer Science and Engineering, CUHK
Projects - Department of Computer Science and Engineering, CUHK

How to build a quantum Newton`s cradle - physicsworld.com
How to build a quantum Newton`s cradle - physicsworld.com

Document
Document

Motivation to Quantum Computing.
Motivation to Quantum Computing.

... The two position states of a photon in a Mach-Zehnder apparatus is just one example of a quantum bit or qubit Except when addressing a particular physical implementation, we will simply talk about “basis” states 0 and 1 ...
Quantum Information Processing (Communication) with Photons
Quantum Information Processing (Communication) with Photons

... • only weak interaction with environment (good coherence) • high-speed (c), low-loss transmission (‘flying qubits’ for longdistance quantum communicati0n) • good single qubit control with standard optical components (waveplates, beamsplitters, mirrors,…) • efficient photon detectors (photodiodes,…) ...
Lecture 14
Lecture 14

Future Computers
Future Computers

... – Put all the input bits in equal superposition of 0 and 1---an equal superposition of all possible inputs. – Run this input through a logic circuit that carries out a particular computation. – The result is a superposition of all the possible outputs of that computation. ...
Another version - Scott Aaronson
Another version - Scott Aaronson

... Theorem: Suppose U implements (say) a computationallyuniversal, reversible cellular automaton. Then after t=exp(n) iterations, C(|t) is superpolynomial in n, unless something very unlikely happens with complexity classes (PSPACEPP/poly) Proof Sketch: I proved in 2004 that PP=PostBQP Suppose C(| ...
CHEMISTRY 1A
CHEMISTRY 1A

... 4. A mixture of 14.0 grams He, 90.0 grams of Ne, and 5.00 mole O2 in a 45.0 liter container has a total pressure of 39.0 atm. Calculate the partial pressure of each gas. ...
Atomic Spectroscopy and the Correspondence Principle
Atomic Spectroscopy and the Correspondence Principle

God Plays Dice
God Plays Dice

... • The mathematical predictions of quantum mechanics yield results that are in agreement with experimental findings. That is the reason we use quantum theory. That quantum theory fits experiment is what validates the theory, but why experiment should give such peculiar results is a mystery. This is t ...
Lecture 1
Lecture 1

... Overview ...
Spin polarized transport in semiconductors – Challenges for
Spin polarized transport in semiconductors – Challenges for

... Propagating surface plasmon polaritons (SPPs) are well-known to have both a subwavelength light confinement and long propagation lengths [1]. For this reason, their interaction with quantum emitters (QEs) has attracted great interest recently. The emergence of Strong Coupling (SC) when an ensemble o ...
vu_quantum_physics_research_report
vu_quantum_physics_research_report

... equations baffled everyone in the scientific community. For some reason, the results of these experiments did not correlate with predictions made by Maxwell in his equations. Among these experiments were the photoelectric effect, which stated that light shined on metal would eject an electron in a q ...
One isotope of beryllium Be undergoes beta minus
One isotope of beryllium Be undergoes beta minus

... ...
Lorentz Invaiance Violation and Granularity of space time
Lorentz Invaiance Violation and Granularity of space time

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Quantum machine learning

Quantum machine learning is a newly emerging interdisciplinary research area between quantum physics and computer science that summarises efforts to combine quantum mechanics with methods of machine learning. Quantum machine learning models or algorithms intend to use the advantages of quantum information in order to improve classical methods of machine learning, for example by developing efficient implementations of expensive classical algorithms on a quantum computer. However, quantum machine learning also includes the vice versa approach, namely applying classical methods of machine learning to quantum information theory.Although yet in its infancy, quantum machine learning is met with high expectations of providing a solution for big data analysis using the ‘parallel’ power of quantum computation. This trend is underlined by recent investments of companies such as Google and Microsoft into quantum computing hardware and research. However, quantum machine learning is still in its infancy and requires more theoretical foundations as well as solid scientific results in order to mature to a full academic discipline.
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